class_docstr: Sammon mapping function
docstr: Compute the Sammon mapping metric for the input data
docstr_tok: ["Compute","the","Sammon","mapping","metric","for","the","input","data"]
code: def _compute_distance(self, x: np.ndarray) -> float:
      """Compute the Sammon mapping metric for the input data"""
      proximity = scipy.spatial.distance_matrix(x, x)
      norm_prox = (proximity - self._proximity) ** 2 / self._proximity_2
      return float(np.sum(norm_prox.ravel()))
  
imports: import numpy
  import pandas
  import scipy.spatial
  from nevergrad.parametrization import parameter
  import nevergrad.common.typing
  from ..base import ExperimentFunction
  from .None import datasets
label_desc: Use image node_id 4 for calling the SammonMapping obj's underlying member method code with example usage: obj._compute_distance(x) and returns: float